Technical Report
Interactive Model-Centric Systems Engineering (IMCSE) - Phase 3
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Systems Engineering and Systems Management Transformation
Report Number: SERC-2015-TR-043-1
Publication Date: 2016-03-01
Project:
Interactive Model-Centric Systems Engineering (IMCSE)
Principal Investigators:
Dr. Donna Rhodes
Co-Principal Investigators:
Dr. Adam Ross
IMCSE advances the current state of SE knowledge in “non-technical” aspects of model-based
engineering. While MBSE and MBE activities are advancing technical aspects of models in the
engineering of systems, this topic advances knowledge relevant to human interaction with
models and model-generated information. It brings relevant knowledge from other fields (e.g.,
cognitive science, visual analytics, data science), placing it in context of systems engineering.
Additionally, this research generates knowledge impacting human effectiveness in model-centric
environments of the future including foundational theory, role of humans in designing/sustaining
these environments and mitigating challenges rooted in cognitive and perceptual considerations.
IMCSE research advances knowledge concerning MPTs that enable reasoning, comprehension
and collaborative decision making in the face of uncertainty, combining artificial and real data,
and effectively utilizing vast amounts of information. New knowledge is created through
normative and descriptive research approaches, leading to prescriptive outcomes that can be
transitioned into practice, as well as educating the workforce. IMCSE research provides support
to SERC’s four thematic research areas, and is most closely aligned with the Systems Engineering
and Management Transformation in regard to decision-making capabilities and leveraging the
capabilities of computation, visualization, and communication for quick and agile response.
Decision-making will be increasingly informed by models, and this research topic strongly
supports MPTs to enable this. There are many past and ongoing research topics that have
relevance for the future of interactive model-centric environments and provide valuable input to
this research.